Classification of Ice Crystal Habits Observed From Airborne Cloud Particle Imager by Deep Transfer Learning-Reference-Cited by-同舟云学术

Classification of Ice Crystal Habits Observed From Airborne Cloud Particle Imager by Deep Transfer Learning

Published:2019-10 Issue:10 Volume:6 Page:1877-1886
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth and Space Science

Author:

Xiao Haixia¹^ORCID,Zhang Feng¹^ORCID,He Qianshan²^ORCID,Liu Pu¹,Yan Fei³,Miao Lijuan⁴⁵,Yang Zhipeng¹

Affiliation:

1. Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster (CIC‐FEMD)Nanjing University of Information Science and Technology Nanjing China

2. Shanghai Key Laboratory of Meteorology and HealthShanghai Meteorological Service Shanghai China

3. Hebei Provincial Weather Modification Office Hebei China

4. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Geographical ScienceNanjing University of Information Science and Technology Nanjing China

5. Department of Structural Development of Farms and Rural AreasLeibniz Institute of Agricultural Development in Transition Economies Halle Germany

Funder

National Natural Science Foundation of China

National Basic Research Program of China

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019EA000636

Reference33 articles.

1. Growth Rates and Habits of Ice Crystals between −20° and −70°C